Sensor System For Dynamic Agriculture Nutrient Application

This disclosure relates to a sensor system, and more particularly, to a sensor system for dynamic agriculture nutrient application.

Selection, application, and timing of nutrients for growing crops is essential in agriculture production. Technology has improved the ability to deliver more precise levels (e.g., amounts) of nutrients to crops, thereby improving the overall yield when harvesting the crops. For example, positioning systems, such as a global positioning system (GPS), may be utilized by farmers to map a nutrient content of the soil within a field. The farmers may then utilize the nutrient map to deliver various amounts of nutrients, such as fertilizer, to particular portions of the field determined to be nutrient deficient based on the nutrient map. As a result, the farmers may no longer need to apply a set amount of the nutrients (e.g., the fertilizer) over the entire field.

In one aspect of the present disclosure, a method is disclosed. The method includes determining, based on data from a first sensor, a first estimated value of a crop health parameter in a first section of a crop and determining, based on data from a second sensor, a second estimated crop value of the health parameter in a second section of the crop. The method also includes measuring, using a third sensor, a measured value of the crop health parameter in the second section, and comparing the second estimated value and the measured value to determine a calibration factor. Additionally, the method includes determining a first product application plan for the first section based upon the first estimated value and the calibration factor.

In certain configurations, the method may further include applying a first product according to the first product application plan to the first section.

In certain configurations, the first estimated value may be a first estimated nutrient level in the first section, the second estimated value may be a second estimated nutrient level in the second section, and the measured value may be a measured nutrient level in the second section.

In certain configurations, the first sensor and the second sensor may be visible light cameras and the third sensor may be a multispectral camera.

In certain configurations, the first sensor and the second sensor may be visible light cameras and the third sensor may be a near-infrared camera.

In certain configurations, the first sensor and the second sensor are multispectral cameras and the third sensor may be a near-infrared camera that includes a calibrated light source.

In certain configurations, the first sensor and the second sensor may be near-infrared cameras and the third sensor may be a near infrared sensor that includes a calibrated light source.

In certain configurations, the method may further include determining a second product application plan for the second section based upon the second estimated value and the calibration factor, and applying a second product according to the second product application plan to the second section.

In certain configurations, the first sensor and the second sensor may form an array of sensors that extends across a working width of a machine, and a width of the first section combined with a width of the second section form the working width of the machine.

In certain configurations, the method may further include detecting, using a height sensor, a height of the crop within the first section. The first product application plan may be further based upon the row width of the crop. The method may also include detecting, using the first sensor, a row width of the crop within the first section. The first product application may be further based upon the row width of the crop.

In another aspect of the present disclosure, a system for agriculture crop health monitoring is disclosed. The system includes a non-transitory memory and a processor configured to execute instructions stored in the non-transitory memory. The processor is configured to execute instructions to determine, based on data from a first sensor, a first estimated value of a crop health parameter in a first section of a crop and determine, based on data from a second sensor, a second estimated value of the crop health parameter in a second section of the crop. The processor is also configured to execute instructions to measure, using a third sensor, a measured value of the crop health parameter in the second section and compare the second estimated value and the measured value to determine a calibration factor. The processor is also configured to execute instructions to determine a first product application plan for the first section based upon the first estimated value and the calibration factor.

In certain configurations, the processor may be further configured to execute instructions to detect, using a height sensor, a height of the crop within the first section and detect, using the first sensor, a row width of the crop within the first section. Determining the first product application plan may be further based upon the height of the crop and the row width of the crop.

In certain configurations, the calibration factor may correspond to a difference between the second estimated value and the measured value.

In certain configurations, the process may be further configured to execute instructions to determine a second product application plan for the second section based upon the second estimated value and the calibration factor and apply a second product according to the second product application plan to the second section.

In certain configurations, the processor may be further configured to execute instructions to determine a second product application plan for the second section based upon the measured value and apply a second product according to the second product application plan to the second section.

In certain configurations, the processor may be further configured to execute instructions to transmit, via a network, information associated with the crop to a controller of a vehicle. The information associated with the crop may include at least one of the first estimated value, the second estimated value, the value, the calibration factor, and the first product application plan.

In certain configurations, the first sensor and the second sensor may be the same type of sensor. The third sensor may be a different type of sensor than the first sensor and the second sensor.

In another aspect of the present disclosure, a system for dynamic agriculture nutrient application is disclosed. The system includes an applicator configured to apply nutrients to a crop and a sensor system in communication with the applicator and configured to monitor the crop. The sensor system includes a first sensor configured to determine a first estimated nutrient level in a first section of the crop, a second sensor configured to determine a second estimated nutrient level in a second section of the crop, and a third sensor configured to measure a measured nutrient level in the second section. The sensor system is configured to compare the second estimated nutrient level and the measured nutrient level to determine a calibration factor, determine a first nutrient application plan for the first section based upon the first estimated nutrient level and the calibration factor, and communicate with the applicator such that the applicator applies first nutrients according to the first nutrient application plan to the first section.

In certain configurations, the calibration factor may correspond to a difference between the second estimated nutrient level and the measured nutrient level. Additionally, the sensor system may be configured to monitor the crop to adjust the first nutrient application plan in real-time.

The present disclosure relates to a sensor system for use with various machinery, providing a cost-effective and accurate way of monitoring crops. The sensor system may be configured for use with agricultural machinery, construction equipment, automotive vehicles, or other types of machinery. By way of example, the sensor system may be configured for use with agricultural machinery, such as a planter machine configured to plant various seeds or a sprayer machine configured to apply one or more products (e.g., nutrients, fertilizers, pesticides, soil amendments, water, or growth regulators) to various crops.

The sensor system may be configured to detect and/or analyze a region surrounding the machinery (e.g., agricultural machinery) being operated. The sensor system may detect objects, movement, environmental conditions, crop conditions (e.g., crop health, crop nutrient levels, etc.), crop dimensions (e.g., crop width, crop height, crop row width, etc.), or a combination thereof, which may be analyzed to determine the performance of the associated machinery and/or to determine an overall condition of the region surrounding the machinery. For example, the sensor system may include one or more imaging sensors that may be configured to capture images and/or videos within a field of view of the sensors (e.g., in the region surrounding the machinery); one or more thermal cameras that may be configured to detect or measure heat patterns; one or more environmental sensors that may be configured to detect or measure environmental conditions (e.g., temperature, humidity, wind, soil moisture, etc.); one or more operational sensors that may be configured to detect or measure operating conditions of the machinery (e.g., movement of the machinery, machinery degradation, fuel levels, speed, GPS location, etc.); one or more other sensors, such as proximity sensors configured to detect obstacles or other machine nearby and/or acoustic sensors configured to identify machinery anomalies through sound analysis; other types of sensors; or a combination thereof.

Conventional crop monitoring may be performed or utilized to determine an overall status of various crops. For example, a nutrient level of the crops, a moisture level of the crops, a health level of the crops (e.g., fungal and/or insect presence), other crop-related parameters, or a combination thereof may be determined based on the crop monitoring. Such monitoring may typically be performed by collecting and evaluating soil samples (i.e., soil sampling). However, while soil sampling may provide information one or more of the above parameters prior to planting, at least some of these parameters often change during the growing season due to, for example, plant usage, growth, leaching, product applications (e.g., fertilizers, fungicides, pesticides, etc.), other factors, or a combination thereof. As such, soil sampling may be unable to provide an accurate measurement of one or more of the above parameters, which may result in overapplication and/or underapplication of various products (e.g., fertilizers, fungicides, or pesticides).

To more accurately measure crop-related parameters, such as those described above, conventional sensor systems may be implemented to monitor the crops throughout the growing season. For example, one or more sensors may be mounted on the machinery (e.g., the agricultural machinery), on mobile equipment such as a drone, or both. Additionally, satellite imaging may be used to monitor the crops throughout the growing season. However, none of these conventional solutions monitor crops in an accurate and repeatable manner. For example, because sensors only detect crop-related parameters within a limited field of view and/or due to variance between particular crops within a field, conventional sensor systems may be unable to consistently and accurately measure the crop-related parameters throughout the entire crop field.

Similarly, environmental conditions and/or positioning of the sensors on the machinery or the mobile equipment may also contribute to variability (e.g., accuracy) of the sensors. For example, the time of day, weather conditions (e.g., cloud coverage, fog, haze), or seasonal changes may affect an angle and/or an amount of sunlight (e.g., full sun, cloudy, shadows being casted by the sun) that reaches the sensors and/or reaches the crops. As a result, visibility of the crops by the sensors may be negatively impacted. Moreover, a direction of travel of the machinery or mobile equipment may also impact the accuracy of the sensors. For example, the sensors may have poor visibility when a direction of travel of the machinery or mobile equipment is directed towards or away from the sun.

To improve on the above challenges, other sampling techniques may be implemented. For example, plant tissue sampling may provide more accurate measurements of crop-related parameters. However, such sampling techniques may be labor intensive, time prohibitive, cost prohibitive, or a combination thereof.

The present teachings provide a sensor system that addresses the aforementioned challenges. The sensor system described herein may be configured to monitor crop-related parameters. The crop-related parameters may include one or more of nutrient levels of crops, a moisture level of the crops, a health level of the crops (e.g., fungal and/or insect presence), other crop-related parameters, or a combination thereof in real-time. The sensor system may also provide real-time feedback to the machinery associated with the sensor system. By way of example, the sensor system may monitor the crops during product (e.g., fertilizer, nutrients, fungicide, pesticide, etc.) application to the crops by an applicator, and the sensor system may provide feedback to the applicator (e.g., to one or more computing devices therein or associated therewith), which can be configured to adjust the application process accordingly. For example, the sensor system may determine a calibration factor, and the calibration factor may be provided to the applicator to adjust a rate of application of the product.

Moreover, the sensor system described herein may use multiple sensors to accurately sense one or more of crop-related parameters in real-time, enabling precise application of products (e.g., fertilizer, nutrients, fungicide, pesticide, etc.) to maximize yield and/or protein content while minimizing excess nutrient application. As a result, the sensor system may reduce overall costs associated with crop cultivation and minimize the environmental impact caused by overapplication of products (e.g., fertilizer, nutrients, fungicide, or pesticide).

1 FIG.A 1 FIG.A 100 100 104 104 102 102 100 100 106 100 100 100 100 Turning now to the figures,illustrates a side view of a machinein accordance with the present teachings. The machinemay include a body 102 and a frame. The framemay form part of the bodyor may support the bodyof the machine. Additionally, the machinemay include a sensor system. As discussed above, the machineis not limited to any specific type of machinery. For example, the machinemay be a vehicle, equipment, other object, or a combination thereof. The machinemay be configured for operation in any type of industry including agriculture, horticulture, , or other types of industry. By way of example, as shown in, the machinemay be an agriculture machine, such as a tractor or applicator that is configured to apply one or more products (e.g., fertilizer, nutrients, fungicide, pesticide, etc.) to crops.

106 100 106 108 100 108 102 104 100 104 110 108 108 100 100 The sensor systemmay be coupled to the machineso that one or more sensors of the sensor system, such as a first sensor, may be positioned to monitor or otherwise interact with an area around the machine. For example, the first sensormay be coupled to the bodyor the frameof the machine, such as along an outer region or outer surface of the frame. Thus, a field of viewof the first sensor(e.g., a field of view of a lens of the first sensor) may extend outboard with respect to the machinealong the ground beneath the machine.

106 100 106 112 114 100 114 100 114 100 114 112 100 116 112 112 114 114 1 FIG.A Alternatively, or additionally, the sensor systemmay be coupled to an accessory or secondary component of the machine. For example, as shown in, the sensor systemmay include a second sensorcoupled to a trailerof the machine. The trailermay be connected to the machineso that the trailermay, for example, be towed or pushed by the machine. For example, the trailermay be an applicator that is configured to apply water, nutrients, fertilizer, pesticides, fungicides, or a combination thereof to the crops. As such, the second sensormay be positioned external to the machineso that a field of viewof the second sensor(e.g., a field of view of a lens of the second sensor) may extend outboard with respect to the traileralong the ground beneath the trailer.

106 108 112 106 100 114 110 108 116 112 100 100 114 100 114 It should be noted that the sensor systemmay include any number of sensors (e.g., zero or more of the first sensor, zero or more of the second sensor, one or more additional sensors, etc.) and may be positioned in any desired manner by adjusting the mounting of the sensor systemto the machineand/or to the trailer. That is, an overall field of view, which may include the field of viewof the first sensorand/or the field of viewof the second sensor, may be configured to capture any desired region around the machine, which may include parts or components of the machineand/or the trailer, surrounding crops, the ground surround the machineand/or the trailer, or a combination thereof.

100 114 114 114 106 100 114 110 108 116 112 108 112 100 100 108 112 106 106 106 100 106 100 106 106 106 100 106 100 By way of example, the machinemay be coupled to the trailerto drive the trailer, where the trailermay be an applicator configured to apply a topical spray to existing crops within a field, such as a pesticide or fertilizer. In this configuration, the sensor systemmay be coupled to the machineand/or the trailerso that the field of viewof the first sensorand/or the field of viewof the second sensorcan monitor the crops within the field. The first sensorand the second sensormay be positioned to monitor various crop-related parameters (e.g., sensor data associated with the crops) and/or monitor operation of the machine(e.g., sensor data associated with the operation of the machine). The first sensorand the second sensormay capture the sensor data associated with the crops, which may then be evaluated by the sensor system(e.g., a computing device within the sensor system) or by a device in communication with the sensor system(e.g., a computing device or system of the machinein communication with the sensor system) to determine a current condition (e.g., health) of the crops. Captured sensor data associated with the operation of the machinemay be evaluated by the sensor system(e.g., a computing device within the sensor system) or a device in communication with the sensor system(e.g., a computing device or system of the machinein communication with the sensor system) to determine the quality of performance of the machine.

1 FIG.B 1 FIG.A 100 114 106 108 112 106 108 112 illustrates a top-down view of the machineand the trailershown in. As discussed above, the sensor systemmay include more than one of the first sensorand/or more than one of the second sensor. In certain configurations, the sensor systemmay not include the first sensoror may not include the second sensor.

1 FIG.B 1 FIG.A 112 112 114 100 114 112 116 112 100 114 106 106 106 100 106 112 106 118 100 106 118 100 By way of example,illustrates an array of the second sensor. The array includes a plurality of the second sensors, which may extend along substantially the entire width of the trailer, as measured transverse to a direction of travel of the machineand the trailerduring operation. Each of the sensors of the array of the second sensorsmay include a field of view that may be similar to the field of viewshown in. As a result, the array of the second sensorsmay monitor and capture data (e.g., data associated with the crops and/or data associated with the operation of the machine) in a surrounding area that extends along the width of the trailer. The captured data may then be evaluated by the sensor system(e.g., a computing device within the sensor system) or a device in communication with the sensor system(e.g., a computing device or system of the machinein communication with the sensor system). For example, the captured data may be initially transmitted from the second sensorsto a controller (not shown) of the sensor system, which may in turn transmit the captured data to a controllerof the machine. In such a case, the controller of the sensor systemand/or the controllerof the machinemay evaluate the captured data.

114 106 114 106 106 106 It should be noted that, while the traileris described in detail above, implementation of the sensor systemis not limited to the trailer. By way of example, the sensor systemmay be implemented on self-propelled machinery, such as a self-propelled sprayer or applicator. For example, the sensor systemmay include one or more sensors that may be positioned along a boom of the self-propelled machinery such that the one or more sensors may be positioned on at least one of a front portion, a rear portion, one or more side portions, a top portion, and a bottom portion of the machinery (e.g., on the boom of the machinery). As such, the sensor systemmay be configured to monitor a direction of travel of the machinery or other directions transverse to the direction of travel of the machinery.

2 FIG. 1 1 FIGS.A andB 200 200 106 100 illustrates a schematic view of another example of a sensor systemin accordance with the present disclosure. The sensor systemmay be similar to the sensor systemof the machinedescribed above and shown in.

200 202 202 114 100 202 100 202 100 202 100 1 1 FIGS.A andB The sensor systemmay be coupled to or otherwise disposed along an apparatusof a machine. For example, the apparatusmay be similar to the trailerof the machinedescribed above and shown in. The apparatusmay be a planting apparatus that is configured to be towed a machine (e.g., the machine) to plant seeds within a field. The apparatusmay also be an applicator that may be coupled to a machine (e.g., the machine) and configured to apply one or more products (e.g., fertilizer, nutrients, fungicide, or pesticide) to crops within a crop field. It should be noted that the apparatusis not particularly limited to any one configuration and may be any component or secondary device in communication with and/or coupled to a machine (e.g., the machine).

2 FIG. 2 FIG. 200 202 200 204 206 208 210 212 214 200 204 214 204 214 236 204 206 238 208 210 204 214 216 200 As shown in, the sensor systemmay include a plurality of sensors disposed along the apparatus. The sensor systemmay include a first sensor, a second sensor, a third sensor, a fourth sensor, a fifth sensor, and a sixth sensor. However, the sensor systemmay include more or fewer sensors than the sensors-shown in. Each of the sensors-may be in communication with at least some of the other sensors (as indicated by the dashed lineextending between the first sensorand the second sensorand the dashed lineextending between the third sensorand the fourth sensor). Each of the sensors-may be in communication with a controllerof the sensor system.

204 214 220 204 214 220 220 220 204 222 220 206 224 220 208 210 226 220 212 228 220 214 230 220 204 214 222 230 204 214 222 230 226 220 208 210 220 222 230 2 FIG. The sensors-may monitor (i.e., may be configured to monitor) a crop. The sensors-may monitor one or more sections of the crop. A section of the cropmay be a defined area or portion (e.g., a row or group of rows) of the crop. By way of example, the first sensormay monitor a first sectionof the crop, the second sensormay monitor a second sectionof the crop, the third sensorand the fourth sensormay monitor a third sectionof the crop, the fifth sensormay monitor a fourth sectionof the crop, and the sixth sensormay monitor a fifth sectionof the crop. A single one of the sensors-may monitor a respective one of the sections-or more than one of the sensors-may monitor a single one of the sections-. For example, as shown in, the third sectionof the cropmay be monitored by both the third sensorand the fourth sensor. In the interest of clarity, as described herein, the cropmay refer to a crop field in its entirety and may include a plurality of plants located within any one of the sections-described above.

204 214 204 214 204 214 200 220 222 230 220 204 214 204 214 204 214 The sensors-may be the same type of sensor or may be different types of sensors. The sensors-may be configured such that the sensors-are contained within or are in communication with one or more image capture devices of the sensor systemto capture still images and/or videos of the cropwithin a respective one of the sections-of the crop. Each of the sensors-may be or may include an image capture device, whereby the sensors-are not limited to any one type of imaging sensor. For example, a sensor of the sensors-may be or may be part of a multispectral camera, a visible light camera, a near-infrared camera, an ultraviolet (UV) camera, a thermal camera, or some other type of camera.

200 204 214 220 222 230 200 204 214 200 200 204 214 204 214 200 204 214 204 214 The sensor systemmay utilize the sensors-to monitor the cropwithin each of the sections-. In particular, the sensor systemmay include different types of sensors and data captured by the sensors-of the sensor systemcan be used to evaluate the overall accuracy of the sensor systemand/or the accuracy of each of the sensors-individually. That is, one or more of the sensors-may be utilized to validate and/or calibrate the sensor systemby validating and/or calibrating at least one of the sensors-based upon the data captured by at least some of the sensors-.

204 206 210 212 214 220 222 230 By way of example, the first sensor, the second sensor, the fourth sensor, the fifth sensor, and the sixth sensormay be the same type of sensor. For example, each of these sensors may be or may be part of a visible light camera, a multispectral camera, or a near-infrared camera. As such, these sensors may be configured to detect and capture data associated with the cropin a similar manner within their respective sections-.

208 204 206 210 212 214 208 208 208 204 214 208 208 204 206 210 212 214 2 FIG. The third sensormay be a different type of sensor than the first sensor, the second sensor, the fourth sensor, the fifth sensor, and the sixth sensor(as indicated by the hatching of the third sensorshown in). For example, whereas the third sensormay be or may be part of a visible light camera, a multispectral camera, or a near-infrared camera, its type must differ from that of the other sensors. In certain configurations the third sensormay be the same type as the other sensors but may be configured differently. For example, all of the sensors-may be or may be part of a near-infrared sensor, whereby the third sensormay include a calibrated light source such that the third sensormay more accurately capture data when compared to the first sensor, the second sensor, the fourth sensor, the fifth sensor, and the sixth sensor.

208 208 204 206 210 212 214 208 220 226 220 210 208 210 200 204 206 208 214 Due to the third sensorbeing a different type of sensor or configured differently than the other sensors, the third sensormay be utilized to calibrate and/or validate the data captured by at least one of the other sensors (e.g., the first sensor, the second sensor, the fourth sensor, the fifth sensor, or the sixth sensor). For example, if the third sensoris configured to more accurately capture data associated with the cropin the third sectioncompared with the data associated to the cropthat is captured by the fourth sensor, the data captured by the third sensormay be compared to the data captured by the fourth sensor. It should also be noted that the sensors may be partitioned into subsets of the sensor system. For example, the first sensorand the second sensormay be a first subset and the sensors-may be a second subset. In this configuration, the first subset and the second subset may each include one sensor that may be of a different type and/or a different configuration compared to the other sensors within their respective subset.

208 210 208 210 208 220 226 220 210 220 226 220 208 210 210 The data captured by both the third sensorand the fourth sensormay be associated with the same crop-related parameter such that the data captured by the third sensormay be compared to the data captured by the fourth sensorto determine a difference therebetween. For example, the data captured by the third sensormay be associated with a nutrient level of the cropin the third sectionof the cropand the data captured by the fourth sensormay also be associated with the nutrient level of the cropin the third sectionof the crop. The data captured by the third sensormay be compared to the data captured by the fourth sensorto determine the accuracy of the fourth sensor.

220 220 220 220 220 220 220 By way of example, the cropmay reflect light (e.g., light from the sun or from an artificial light source) in various distinct patterns based upon a physiological state of the crop(e.g., health of the cropor stress of the cropdue to a lack of nutrients or other crop-related parameters). That is, the pattern of light reflected by the cropmay vary based upon a current physiological condition of the cropand may provide specific signatures (e.g., spectral signatures) associated with different physiological conditions (e.g., nutrient levels) of the crop.

208 208 226 220 200 200 220 226 To capture the aforementioned spectral signatures, the third sensormay be or may be part of a multispectral camera that is configured to capture data in the form of one or more images in multiple spectral bands at wavelengths across a range of the electromagnetic spectrum, including visible light (e.g., wavelengths of about 380 nm to about 750 nm) and near-infrared (e.g., wavelengths of about 750 nm to about 1400 nm). The third sensormay capture the light that is reflected off of the third sectionof the cropin the form of one or more images, and the captured image(s) may be evaluated by the sensor systemor a system in communication with the sensor systemto determine the physiological state of the cropwithin the third section.

208 226 220 For example, the captured image(s) by the third sensormay be evaluated to identify the specific spectral signatures within the third sectionof the crop. Evaluation of the captured image(s) may include, for example, analyzing the image(s) to identify any distinct reflectance patterns, determining one or more reflectance values based upon the captured image(s), and calculating one or more crop-related parameters based upon the determined reflectance value(s).

210 210 226 220 200 200 220 220 226 210 208 210 210 220 226 210 208 Additionally, the fourth sensormay be or may be part of a visible light camera that is configured to capture data in the form of one or more images only in the visible light spectral band (e.g., wavelengths of about 380 nm to about 750 nm). The fourth sensormay capture the light that is reflected off of the third sectionof the cropin the form of one or more images, and the captured image(s) may be evaluated by the sensor systemor a system in communication with the sensor systemto determine the physiological state of the crop(e.g., the overall physiological state of the cropbased upon the crop-related parameters) within the third section. Evaluation of the image(s) captured by the fourth sensormay be similar to the evaluation of the image(s) captured by the third sensor. However, due to the fourth sensorbeing unable to capture images in spectral bands other than the visible light spectral band (e.g., unable to capture images in the near-infrared spectral band), evaluation of the images captured by the fourth sensormay be unable to identify certain physiological conditions of the cropwithin the third section. For example, if certain spectral signatures are only present in the near-infrared spectral band, such spectral signatures would not be identified by evaluating the image(s) captured by the fourth sensorand may only be identified by evaluating the image(s) captured by the third sensor.

208 210 208 210 208 210 210 Due to the above potential discrepancies between the evaluation of the image(s) captured by the third sensorand the image(s) captured by the fourth sensor, the third sensormay be considered more accurate when compared to the fourth sensorand its captured image(s). As a result, the image(s) captured by the third sensorand/or data extracted therefrom (e.g., distinct reflectance patterns, one or more reflectance values, or one or more crop-related parameters) may be compared to the image(s) captured by the fourth sensorand/or data extracted therefrom (e.g., distinct reflective patterns, one or more reflectance values, or one or more crop-related parameters) to determine an accuracy of the fourth sensor.

210 204 206 212 214 210 As discussed above, the fourth sensormay be the same type or configuration of sensor as the first sensor, the second sensor, the fifth sensor, and the sixth sensor. As such, the accuracy determined for the fourth sensorbased upon the above evaluation may be used to determine a calibration factor to formulate tailored product (e.g., fertilizer, fungicide, or pesticide) application plans for different crop sections.

232 200 208 210 232 202 202 222 230 202 232 222 230 222 230 232 222 230 200 For example, a controllerof the sensor systemmay compare the image(s) captured by the third sensorand/or data extracted therefrom to the image(s) captured by the fourth sensorand/or data extracted therefrom to determine the calibration factors to adjust the an application plans for different crop sections The controllermay also communicate with other components of the apparatusto modify one or more operating parameters of the apparatusin each of the sections-based upon the calibration factor. For example, the apparatusmay be an applicator and the controllermay communicate to a portion of the applicator (e.g., a sprayer) located in each of the sections-to modify an application rate in each of the sections-based upon the calibration factor. Thus, the controllermay selectively and differently modify application parameters of a product within at least some of the sections-based on the data captured by the sensor systemand based upon a comparison of the data as described above.

232 202 234 100 234 118 100 234 204 214 234 100 234 232 200 204 214 204 214 202 100 202 234 232 200 1 1 FIGS.A andB The controllerof the apparatusmay also be in communication with a machine controllerof the machine (e.g., the machine). The machine controllerof the machine may be similar to the controllerof the machineshown in. The machine controllerof the machine may receive the data captured by the sensors-for evaluation. The machine controllermay then provide such data to a user of the machine (e.g., the machine), such as an operator, via a display or other means of communication. Additionally, the machine controllermay communicate with the controllerof the sensor systemto operate the sensors-, modify one or more operating parameters of the sensors-, modify one or more operating parameters of the apparatus, or a combination thereof. Thus, the machine (e.g., the machine) may maintain communication with the apparatusbased upon communication between the machine controllerof the machine and the controllerof the sensor system.

3 FIG. 1 1 FIGS.A andB 2 FIG. 300 300 302 106 200 To describe some implementations of the sensor systems described herein,is a diagram of an example of a systemto further illustrate the electronic computing and communication of the sensor systems described herein. For example, the systemmay include a sensor system, which may be or may be similar to the sensor systemshown inor the sensor systemshown in.

30 304 302 306 304 302 The sensor systemmay include one or more computing devices, such as a controllerof the sensor system, a machine controllerin communication with the controllerof the sensor system, or both.

300 308 310 308 310 108 112 106 204 214 200 308 312 314 308 312 220 308 308 314 220 308 304 302 1 1 FIGS.A andB 2 FIG. The systemmay include one or more sensors, such as a first sensorand a second sensor. The first sensorand the second sensormay be similar to the first sensorand/or the second sensorof the sensor systemshown inor may be similar to the sensors-of the sensor systemshown in. By way of example, the first sensormay include an emitterand a receiver. The first sensormay be or may be part of an image sensor module (e.g., a camera) such that the emittermay transmit light to a portion of a crop (e.g., the crop) within a field of view of the first sensor. The light may reflect off the crop within the field of view of the first sensorand be captured by the receiverin the form of one or more images. The captured image(s) may then be further evaluated to determine a physiological state and/or condition of the cropwith the field of view of the first sensor, such as by identifying distinct reflectance patterns, determining one or more reflectance values based upon the captured image(s), and calculating one or more crop-related parameters based upon the determined reflectance value(s). Such evaluation may be completed by the controllerof the sensor system.

310 308 310 316 318 316 220 310 310 318 308 220 308 304 302 The second sensormay be or may be part of an image sensor module (e.g., a camera) that may be similar or different from the first sensor. The second sensormay include an emitterand a receiver. The emittermay transmit light to a portion of a crop (e.g., the crop) within a field of view of the second sensor. The light may reflect off the crop within the field of view of the second sensorand be captured by the receiverin the form of one or more images. The captured image(s) may then be evaluated similar to the captured image(s) of the first sensorto determine a physiological state and/or condition of the cropwith the field of view of the first sensor. Such evaluation may be completed by the controllerof the sensor system.

304 320 320 304 320 320 308 310 The controllermay be or may include a processor, such as a microprocessor, and may include a single processor or multiple processors. A processor may have a single processing core or multiple processing cores. Alternatively, the processormay include other types of devices, or multiple devices, not existing or hereafter developed, configured for manipulating or processing information. The controllermay include multiple processors interconnected in one or more manners, including but not limited to, hardwired or networked (e.g., wirelessly networked). By way of example, the operations of the processormay be distributed across multiple devices or units that may be coupled directly or via a local area or other suitable network. The processormay also include a cache or cache memory for local storage of operating data or instructions associated with the evaluation (e.g., further processing) of the data captured by the first sensorand/or the second sensor.

304 322 322 322 322 322 304 The controllermay also include a memory. The memorymay include one or more memory components, which may each be volatile memory or non-volatile memory. For example, the volatile memory of the memorymay be random access memory (RAM)(e.g., a DRAM module, such as DDR SDRAM) or another form of volatile memory. In another example, the non-volatile memory of the memorymay be a disk drive, a solid-state drive, flash memory, phase-change memory, or another form of non-volatile memory configured for persistent electronic information storage. The memorymay also include other types of devices, now existing or hereafter developed, configured for storing data or instructions for processing by the processor of the controller.

322 304 322 320 304 304 308 310 The memorycan include data for immediate access by the controller. For example, the memorymay include executable instructions, application data, an operating system, or a combination thereof accessible by the processorof the controller. The executable instructions, the application data, the operating system, or a combination thereof may be loaded or copied, in whole or in part, from non-volatile memory to volatile memory to be executed by the controller. For example, the executable instructions and application data may include instructions and data for evaluating the data captured by the first sensorand/or the second sensor.

322 324 304 302 324 324 304 302 304 308 310 304 302 306 324 326 306 324 The memorymay include executable instructions or application data associated with a communication deviceof the controllerof the sensor system. The communication devicemay be or may include a transmitter and/or a receiver. The communication devicemay facilitate communication between the controllerof the sensor systemand the controllerof the machine. For example, the data (e.g., the images) captured by the first sensorand/or the second sensormay be evaluated by the controllerof the sensor system, and results of such evaluation may be transmitted to the machine controllerfor review by an operator of the machine. The communication devicemay communication with a communication deviceof the machine controller, which may be similar to or different than the communication device.

304 328 328 302 302 In certain configurations, the controllermay include a user interface. The user interfacemay include one or more input interfaces and/or output interfaces. An input interface may be, for example, a positional input device, such as a mouse, touchpad, touchscreen, or the like; a keyboard; or another suitable human or machine interface device. An output interface may be, for example, a display, such as a liquid crystal display, a cathode-ray tube, a light emitting diode display, or other suitable display. Thus, the operator may interact with the sensor systemto monitor and/or operate the sensor system.

302 306 302 100 306 308 310 304 306 308 310 306 304 302 326 306 306 330 332 334 330 320 304 332 322 304 334 328 304 306 302 1 1 FIGS.A andB As discussed above, the sensor systemmay be in communication with the machine controllerof a machine that is coupled to, or that is in communication with, the sensor system. The machine may be similar to the machineshown in. The machine controllermay receive and/or evaluate the data captured by the first sensor, the second sensor, or both. For example, the controllerand/or the machine controllermay receive the images captured by the first sensorand the second sensorfor evaluation (e.g., to identify distinct reflectance patterns, determine one or more reflectance values based upon the captured images, and calculate one or more crop-related parameters based upon the determined reflectance value(s)). The machine controllermay receive data from, or transmit data to, the controllerof the sensor systemvia the communication deviceof the machine controller. The machine controllermay also include a processor, a memory, and a user interface. The processormay be similar to the processorof the controller. The memorymay be similar to the memoryof the controller. The user interfacemay be similar to the user interfaceof the controllersuch that an operator may interface with the machine controllerto operate the machine, operator the sensor system, or both.

304 306 336 336 304 302 306 334 328 336 302 306 300 The controllerand the machine controllermay be in communication via a network. The networkmay be or may include, for example, the Internet, a local area network (LAN), a wide area network (WAN), a virtual private network (VPN), or another public or private means of electronic computer communication capable of transferring data between the controllerof the sensor systemand the machine controller. In some implementations, an operator, via the user interfaceand/or via the user interface, may connect to the networkvia a communal connection point, link, or path, or using a distinct connection point, link, or path. For example, a connection point, link, or path can be wired, wireless, use other communications technologies, or a combination thereof. Additionally, it should be noted that the sensor system, the machine controller, or other elements of the systemmay include network hardware such as routers, switches, other network devices, or a combination thereof.

4 FIG. 1 1 FIGS.A andB 2 FIG. 3 FIG. 400 400 106 200 300 400 106 200 300 400 illustrates an example of a processfor agriculture product application using a sensor system. The processmay be applicable to the sensor systemillustrated in, the sensor systemillustrated in, or the systemillustrated in. In other words, the processmay be implemented, at least in part, by one of the sensor system, the sensor system, or the system. The processcan be used to detect and estimate crop health parameters using multiple sensors to determine calibration factors to adjust and formulate tailored product application plans for different crop sections based on the calibration factors, thereby leading to precise and individualized product application to maximize crop health and yield while minimizing excess use of resources.

400 400 400 320 400 330 306 300 3 FIG. 3 FIG. The processcan be performed, for example, by executing a machine-readable program or other computer-executable instructions, such as routines, instructions, programs, or other code. The steps, or operations, of the processmay be implemented directly in hardware, firmware, software executed by hardware, circuitry, or a combination thereof. The processcan be executed by a processor (e.g., the processorof) associated with or included in the sensor system. The processcan also be executed by a processor (e.g., the processorof) of a system in communication with the sensor system (e.g., the machine controllerof the system).

402 200 402 220 200 220 222 230 220 2 FIG. 2 FIG. Initial operation of the sensor system may begin at operationto begin detection of a crop within a field. For illustrative purposes and with reference to, the initial operation of the sensor systemmay begin at operationto detect one or more parameters (i.e., crop-related parameters) associated with the crop. The sensor systemmay begin detection of one or more parameters associated with the cropin one or more of the sections-of the cropshown in.

222 404 404 200 220 222 204 2 FIG. The sensor system may detect a crop health parameter in a first section of the crop (e.g., the first sectionshown in) at operation. The crop health parameter may be any parameter or feature detected by the sensor system that is associated with the crop. For example, the crop health parameter, may be a nutrient level, a moisture level, a fungal pressure, an insect pressure, a crop height, a crop width, other parameters associated with a health of the crop, or a combination thereof. The crop health may be detected at operationusing (e.g., based on data captured by) one or more of the sensors. For example, with respect to the sensor system, the crop health parameter of the cropin the first sectionmay be detected based upon one or more images captured by the first sensor.

404 406 204 200 220 222 232 200 220 222 204 214 208 Detection of the crop health parameter in the first section at operationmay also include estimating the crop health parameter at operation. That is, during or after detection of the crop health parameter, the sensor system may capture data (e.g., images) associated with the crop health parameter to estimate a value of the crop health parameter. Estimation of the value of the crop health parameter may be based upon evaluation of the images captured by the sensor system. For example, the images captured by one or more of the sensors within the sensor system may be evaluated to identify distinct reflectance patterns of the crop within the first section, determine one or more reflectance values based upon the captured images, and calculate one or more crop-related parameters based upon the determined reflectance value(s)). By way of example, the first sensorof the sensor systemmay capture images associated with the crop health parameter of the cropin the first sectionso that the controllerof the sensor systemmay estimate a value of the crop health parameter of the cropin the first section. That is, the value of the crop health parameter based upon the images captured by any of the sensors-, except for the third sensor, may be considered the estimated value of the crop health parameter.

224 230 220 408 404 504 508 2 FIG. The sensor system may detect a crop health parameter in a second section of the crop (e.g., any additional one of the sections-of the cropshown in) at operation. The crop health parameter may be the same crop health parameter detected in the first section at operation. That is the crop health parameter detected in the first section at operationmay be the same as the crop health parameter detected in the second section at operation.

408 410 412 406 210 220 226 232 200 220 226 210 Detection of the crop health parameter in the second section at operationmay include estimating the crop health parameter at operationand measuring the crop health parameter at operation. That is, during or after detection of the crop health parameter, the sensor system may capture data (e.g., images) associated with the crop health parameter to estimate a value of the crop health parameter and also measure the value of the crop health parameter. Estimation of the value of the crop health parameter may be similar to the estimation completed at operation. By way of example, the fourth sensormay capture images associated with the crop health parameter of the cropin the third sectionso that the controllerof the sensor systemmay estimate a value of the crop health parameter of the cropin the third section. That is, the value of the crop health parameter based upon the images captured by the fourth sensormay be considered the estimated value of the crop health parameter.

208 220 226 232 200 220 226 208 210 208 210 208 208 200 Additionally, the third sensormay also capture images associated with the crop health parameter of the cropin the third sectionso that the controllerof the sensor systemmay measure a value of the crop health parameter of the cropin the third section. As discussed above, the third sensorand the fourth sensormay be different sensors such that a value of the crop health parameter (e.g., nutrients level) based upon the images captured by the third sensormay be more accurate than a value of the crop health parameter (e.g., nutrients level) based upon the images captured by the fourth sensor. That is, the value of the crop health parameter that is determined based upon the images captured by the third sensormay reflect the actual value of the crop health parameter. That is, the value of the crop health parameter based upon the images captured by the third sensormay be considered a measured value of the crop health parameter while the value of the crop health parameter based upon the images captured by any of the other sensors within the sensor systemmay be considered an estimated value of the crop health parameter.

406 410 412 414 232 304 234 306 406 410 412 2 FIG. 3 FIG. 2 FIG. 3 FIG. After estimation and measurement of the crop health parameter at operations,, and, a calibration factor may be determined at. The calibration factor may be determined by a controller (e.g., the controllerofor the controllerof, the machine controllerofor the machine controllerof, or both). The calibration factor may be determined based upon the estimated crop health parameter of the first section of the crop obtained at operation, the estimated crop health parameter of the second section of the crop obtained at operation, the measured crop health parameter of the second section of the crop obtained at operation, or a combination thereof.

410 412 410 412 414 By way of example, the estimated crop health parameter obtained at operationmay be compared to the measured crop health parameter obtained at operation. For example, the estimated crop health parameter obtained at operationmay be compared to the measured crop health parameter obtained at operationto determine a difference in value therebetween. The difference may indicate how much greater or smaller the estimated value of the crop health parameter is compared to the measured crop health parameter. As a result, at operation, the calibration factor may be determined to define a configuration value. That is, the calibration factor may be a configuration value that at least partially adjusts a product (e.g., fertilizer, fungicide, or pesticide) application plan in a particular section of the crop.

414 410 412 410 412 204 406 410 210 406 By way of example, the calibration factor determined at operationmay establish that the estimated crop health parameter at operationfor the second section of the crop is approximately 10% greater in value than the measured crop health parameter obtained at operation. In such a case, the calibration factor may be used to adjust a value of the estimated crop health parameter atsuch that the value of the estimated crop health parameter is equal to the measured crop health parameter at. Similarly, since the sensor (e.g., the first sensor) used at operationis the same type of sensor used at operation(e.g., the fourth sensor), the calibration factor may also adjust a value of the estimated crop health parameter obtained at operationto accommodate for any inaccuracy (e.g., the approximately 10% greater estimated value). The adjusted values may then be utilized to determine product application plans for specific sections of the crop. Alternatively, in lieu of adjusting the value of the estimated crop health parameter based upon the calibration factor to adjust the product application plans, the calibration factor may adjust the product application plans (e.g., operating parameters of the product application plans) directly.

412 208 414 222 230 208 200 208 208 The measured crop health parameter at operation, which may be obtained by a more accurate sensor (e.g., the third sensor), may be used to determine the calibration factor at operationto adjust measurements of a crop health parameter across all sections being detected (e.g., the sections-). That is, the third sensormay provide a “ground truth” to calibrate data captured by the remaining sensors in the sensor system (e.g., the sensor system) to adjust the product application plans. As such, more economical (e.g., cost effective) or different sensors may be used in the sensor system without a loss of accuracy due to the presence of a more accurate sensor (e.g., the third sensor). That is, the use of more economical of different sensors in conjunction with the more accurate sensor (e.g., the third sensor) may not negatively impact any product application plan that is based upon the estimated crop health parameter. For example, the calibration factor, may be implemented to adjust a product application plan to minimize overapplication and/or underapplication of a particular product.

414 416 200 220 222 222 220 418 416 Once the calibration factor is determined at operation, a product application plan as discussed above is determined atfor the first section of the crop. The product application plan may be determined by the controller. The product application plan may be or include a process or parameters of application of one or more products to the crop within the first section of the crop. For example, the sensor systemmay be coupled to an applicator, and the product application plan may include operating conditions of the applicator to apply one or more products to the cropwithin the first section. The one or more products may be fertilizer, nutrients, pesticides, fungicides, water, other topical applications, or a combination thereof. The product application plan may include an application rate, the types of products to be applied, operating conditions of the machine (e.g., speed, direction, ride height, etc.), other operating parameters, or a combination thereof. The product or products may be applied to the first section of the crop (e.g., the first sectionof the crop) at operationin accordance with the application plan determined at operation.

414 420 416 420 416 226 220 422 420 Additionally, once the calibration factor is determined at operation, a product application plan for the second section of the crop is determined at. The product application plan may be determined by the controller. The product application plan may include a process or parameters of application of one or more products to the crop within the second section of the crop, such as described above with respect to operation. The product application plan determined atmay be different from the product application plan determined at. As such, product application for each of the sections of the crop may be tailored and individualized. The product or products may then be applied to the second section of the crop (e.g., the third sectionof the crop) at operationin accordance with the application plan determined at operation.

5 FIG. 1 1 FIGS.A andB 2 FIG. 3 FIG. 500 500 106 200 300 500 106 200 300 500 illustrates another example of a processfor agriculture product application using a sensor system. The processmay be applicable to the sensor systemillustrated in, the sensor systemillustrated in, or the systemillustrated in. In other words, the processmay be implemented, at least in part, by one of the sensor system, the sensor system, or the system. The processcan be used to detect and estimate a nutrient level of the crop using multiple sensors to determine calibration factors to adjust and formulate tailored product (e.g., fertilizer or other nutrient application) plans for different crop sections based on the calibration factors, thereby leading to precise and individualized product application to maximize crop health and yield while minimizing excess use of resources.

500 500 500 320 500 330 306 300 3 FIG. 3 FIG. The processcan be performed, for example, by executing a machine-readable program or other computer-executable instructions, such as routines, instructions, programs, or other code. The steps, or operations, of the processmay be implemented directly in hardware, firmware, software executed by hardware, circuitry, or a combination thereof. The processcan be executed by a processor (e.g., the processorof) associated with or included in the sensor system. The processcan also be executed by a processor (e.g., the processorof) of a system in communication with the sensor system (e.g., the machine controllerof the system).

500 400 502 502 402 400 The processmay be similar to the processdescribed above and is intended to illustrate an example of a crop health parameter detected by the sensor system. Initial operation of the sensor system may begin at operation. Initiating operation of the sensor system may begin detection of a crop within a field. Initiating operation of the sensor system at operationmay be similar to initiating operation of the sensor system at operationof the process.

222 504 504 200 220 222 204 504 506 506 406 410 400 204 222 220 232 232 220 222 2 FIG. The sensor system may detect a nutrient level in a first section of the crop (e.g., the first sectionof the crop shown in) at operation. The nutrient level may be detected at operationusing (e.g., based on data captured by) one or more of the sensors. For example, with respect to the sensor system, the nutrient level of the cropin the first sectionmay be detected based upon one or more images captured by the first sensor. Detection of the nutrient level at operationmay also include estimating the nutrient level at operation. Estimating the nutrient level at operationmay be similar to the estimation completed at operationor operationof the process. For example, the first sensormay capture one or more images of the first sectionof the crop, and the image(s) may be evaluated by the controllerto determine the nutrient level. That is, the controllermay be configured to identify distinct reflectance patterns of the cropwithin the image(s) that may be indicative of a particular nutrient level of the crop within the first section.

224 230 220 508 508 510 512 410 400 506 412 400 208 210 2 FIG. The sensor system may also detect a nutrient level in a second section of the crop (e.g., any additional one of the sections-of the cropshown in) at operation. Detection of the nutrient level in the second section at operationmay include estimating the nutrient level at operationand measuring the nutrient level at operation. That is, during or after detection of the nutrient level, the sensor system may capture data (e.g., images) associated with the nutrient level to estimate the nutrient level and also measure the nutrient level. Estimation of the nutrient level in the second section may be similar to the estimation completed at operationof the processor at operation. Measurement of the nutrient level in the second section may be similar to the measurement completed at operationof the process. For example, as discussed above, the measured nutrient level (i.e., a measured crop health parameter) may be a nutrient level that is based upon the image(s) captured by the third sensor, whereas the estimated nutrient level (i.e., an estimated crop health parameter) may be a nutrient level that is based upon the image(s) captured by the fourth sensor.

506 510 512 514 232 304 234 306 414 400 512 510 2 FIG. 3 FIG. 2 FIG. 3 FIG. After estimation and measurement of the nutrient levels at operation,, and, a calibration factor may be determined at. The calibration factor may be determined by a controller (e.g., the controllerofor the controllerof, the machine controllerofor the machine controllerof, or both). The calibration factor may be determined in a similar manner to the calibration factor determined atin the processdescribed above. For example, the calibration may be determined by comparing the measured nutrient level obtained at operationto the estimated nutrient level obtained at operation.

514 516 416 400 518 516 Once the calibration factor is determined at operation, a nutrient application plan for the first section of the crop is determined at. The nutrient application plan may be determined by the controller. The nutrient application plan may be a method or parameters of nutrient application within the first section of the crop, which may be similar to the product application plan determined at operationof the process. The nutrients may be applied to the first section of the crop at operationin accordance with the application plan determined at operation.

514 520 420 400 522 520 Additionally, once the calibration factor is determined at operation, a nutrient application plan for the second section of the crop is determined at. The nutrient application plan may be determined by the controller. The nutrient application plan may be a method or parameters of nutrient application to the crop within the second section of the crop, which may be similar to the product application plan determined at operationof the process. The nutrients may then be applied to the second section of the crop (at operationin accordance with the application plan determined at operation.

6 FIG. 1 1 FIGS.A andB 2 FIG. 3 FIG. 600 600 106 200 300 600 106 200 300 500 600 600 illustrates another example of a processagriculture product application using a sensor system. The processmay be applicable to the sensor systemillustrated in, the sensor systemillustrated in, or the systemillustrated in. In other words, the processmay be implemented, at least in part, by one of the sensor system, the sensor system, or the system. Similar to the processdescribed above, the processcan be used to detect and estimate a nutrient level of the crop using multiple sensors to determine calibration factors to adjust and formulate tailored nutrient application plans. In this particular case, the processmay also use crop height and/or crop row width to formulate the nutrient application plans.

600 500 600 320 600 330 306 300 3 FIG. 3 FIG. The processcan be performed, for example, by executing a machine-readable program or other computer-executable instructions, such as routines, instructions, programs, or other code. The steps, or operations, of the processmay be implemented directly in hardware, firmware, software executed by hardware, circuitry, or a combination thereof. The processcan be executed by a processor (e.g., the processorshown in) associated with or included in the sensor system. The processcan also be executed by a processor (e.g., the processorof) of a system in communication with the sensor system (e.g., the machine controllerof the system).

600 400 500 602 502 The processmay be similar to the processand the processdescribed above and is intended to illustrate another example of a crop health parameter detected by the sensor system. Initiating operation of the sensor system at operationmay be similar to initiating operation of the sensor system at operation.

222 604 604 604 606 606 506 400 2 FIG. The sensor system may detect a nutrient level in a first section of the crop (e.g., the first sectionof the crop shown in) at operation. The nutrient level may be detected at operationusing (e.g., based on data captured by) one or more of the sensors. Detection of the nutrient level at operationmay also include estimating the crop health parameter at operation. Estimating the nutrient level at operationmay be similar to the estimation completed at operationof the process.

224 230 220 608 608 610 612 510 500 512 500 208 210 2 FIG. The sensor system may also detect a nutrient level in a second section of the crop (e.g., any additional one of the sections-of the cropshown in) at operation. Detection of the nutrient level in the second section at operationmay include estimating the nutrient level at operationand measuring the nutrient level at operation. That is, during or after detection of the nutrient level, the sensor system may capture data (e.g., images) associated with the nutrient level to estimate the nutrient level and also measure the nutrient level. Estimation of the nutrient level in the second section may be similar to the estimation completed at operationof the process. Measurement of the nutrient level in the second section may be similar to the measurement completed at operationof the process. For example, as discussed above, the measured nutrient level (i.e., a measured crop health parameter) may be a nutrient level that is based upon the image(s) captured by the third sensor, whereas the estimated nutrient level (i.e., an estimated crop health parameter) may be a nutrient level that is based upon the image(s) captured by the fourth sensor.

600 614 616 The processmay also include detecting a crop height of the crop within the first section at operationand detecting a row width of the first section of the crop at operation. The crop height and the row width may be detected by one or more sensors of the sensor system and/or by one or more additional sensors, such as an additional height or width detection sensor that is part of the sensor system or in communication with the sensor system.

By way of example, one or more sensors may capture multiple, overlapping images of the crop within the first section from different angles. The images may then be evaluated by the processor of the sensor system or the machine processor in communication with the sensor system to identify common points between the overlapping images, and the common points may then be utilized to reconstruct a three-dimensional model of the first section of the crop. The three-dimensional model may then be measured to determine the crop height and/or the row width. Additionally, or alternatively, one or more sensors may implement light detection and ranging (LiDAR) to emit laser pulses towards the first section of the crop. The one or more sensors may detect the reflected laser pulses from the ground and the crop to determine distances, and the determined distances may then be utilized to reconstruct a three-dimensional model of the first section of the crop. The three-dimensional model may then be measured to determine the crop height and/or the row width.

600 618 620 618 614 620 616 The processmay further include detecting a crop height of the crop within the second section at operationand detecting a row width of the second section of the crop at operation. The crop height and the row width may be detected by one or more sensors of the sensor system and/or by one or more additional sensors, such as an additional height or width detection sensor that is part of the sensor system or in communication with the sensor system. Determining the crop height at operationmay be similar to determining the crop height at operation. Determining the row width at operationmay be similar to determining the row width at operation.

622 414 400 514 500 614 620 After detection of the crop height and row width of both the first section and the second section, a calibration factor may be determined at. The calibration factor may be determined by a controller of the sensor system by a machine controller of a machine in communication with the sensor system, or both. The calibration factor may be determined in a similar manner to the calibration factor determined atin the processand/or the calibration factor determined atin the processdescribed above. Additionally, the calibration factor may also utilize the crop height and/or row width determined for both the first section and the second section of the crop based upon operations-. That is, the calibration factor may be determined at least partially based upon the nutrient level, crop height, and row width determined in the first section and the second section.

622 624 516 500 626 624 Once the calibration factor is determined at operation, a nutrient application plan for the first section of the crop is determined at. The nutrient application plan may be determined by the controller. The nutrient application plan may be a method or parameters of nutrient application within the first section of the crop, which may be similar to the nutrient application plan determined at operationof the process. The nutrients may be applied to the first section of the crop at operationin accordance with the application plan determined at operation.

622 628 520 630 628 Additionally, once the calibration factor is determined at operation, a nutrient application plan for the second section of the crop is determined at. The nutrient application plan may be determined by the controller. The nutrient application plan may be a method or parameters of nutrient application to the crop within the second section of the crop, which may be similar to the product application plan determined at operation. The nutrients may then be applied to the second section of the crop at operationin accordance with the application plan determined at operation.

7 FIG. 1 1 FIGS.A andB 2 FIG. 3 FIG. 700 700 106 200 300 700 106 200 300 illustrates an example of a processof agriculture product application using a sensor system. The processmay be performed with respect to and/or by the sensor systemillustrated in, the sensor systemillustrated in, or the systemillustrated in. In other words, the processmay be at least partially completed by the sensor system, the sensor system, or the system.

700 700 700 320 302 700 330 306 300 700 400 500 600 3 FIG. The processcan be performed, for example, by executing a machine-readable program or other computer-executable instructions, such as routines, instructions, programs, or other code. The steps, or operations, of the processmay be implemented directly in hardware, firmware, software executed by hardware, circuitry, or a combination thereof. The processcan be executed by a processor (e.g., the processorof the sensor systemshown in) associated with or included in the sensor system. The processcan also be executed by a processor (e.g., the processor) of a system in communication with the sensor system (e.g., the machine controllerof the system). The processmay be similar to the processes,, anddescribed above.

700 702 204 200 232 222 220 The processincludes determining a first estimated value of a crop health parameter in a first section of a crop at step. The crop health parameter may be any parameter associated with the crop, such as a nutrient level, moisture level, fungal presence, insect presence, or other crop health parameter. The first estimated value of the crop health parameter may be determined based on data (e.g., images) obtained from a first sensor. For example, the first sensorof the sensor systemmay obtain data, which may in turn be evaluated by the controllerto estimate the value of the crop health parameter (e.g., nutrient level) in the first sectionof the crop.

700 704 210 200 232 226 220 The processmay also include determining a second estimated value of the crop health parameter in a second section of the crop at step. The second estimated value of the crop health parameter may be determined based on data (e.g., images) obtained from a second sensor. For example, the fourth sensorof the sensor systemmay obtain data, which may in turn be evaluated by the controllerto estimate the value of the crop health parameter (e.g., nutrient level) in the third sectionof the crop.

706 208 200 232 226 220 The method may also include measuring a measured value of the crop health parameter in the second section of the crop at step. The measured value of the crop health parameter may be determined based on data (e.g., images) obtained from a third sensor. For example, the third sensorof the sensor system, which may be a different type of sensor than the first sensor and the second sensor, may obtain data, which may in turn be evaluated by the controllerto measure the crop health parameter (e.g., nutrient level) in the third sectionof the crop.

708 400 500 600 The method may further include comparing the second estimated value and the measured value to determine a calibration factor at step. The calibration factor may be determined similar to the calibration factor of the process, the calibration factor of the process, and the calibration factor of the processdescribed above.

708 710 400 712 700 712 After determining the calibration factor at step, a first product application plan for the first section may be determined at step. The first product application plan may be based upon the first estimated value and the calibration factor. The first product application plan may be similar to the product application plan of the processdescribed above, whereby a product or products (e.g., nutrients) may be applied to the first section of the crop based upon the first product application plan at step. However, in certain implementations, the processmay not include the step.

4 7 FIGS.- 2 FIG. 4 7 FIGS.- 222 230 220 204 214 202 222 230 202 It should also be noted that whilediscussed above reference a first section and a second section of the crop, the processes and methods above may also be implemented in any number of sections of the crop. For example, with respect to, the processes and methods discussed with respect tomay be implemented in all or a portion of the sections-of the crop. The sensors-may form an array of sensors that extend across a working width of the apparatus. That is, a combined width of each of the sections-may form the working width of the apparatus, and the array of sensors may be used to determine various crop health parameters along a portion or an entirety of the working width.

While the disclosure has been described in connection with certain embodiments of a sensor system, it is to be understood that the disclosure is not limited to or by the disclosed embodiments but, on the contrary, is intended to cover various modifications and equivalent arrangements included within the scope of the appended claims, which scope is to be accorded the broadest interpretation so as to encompass all such modifications and equivalent structures as is permitted under the law.

Persons skilled in the art will understand that the various embodiments of the present disclosure and shown in the accompanying figures constitute non-limiting examples, and that additional components and features may be added to any of the embodiments discussed hereinabove without departing from the scope of the present disclosure. Additionally, persons skilled in the art will understand that the elements and features shown or described in connection with one embodiment may be combined with those of another embodiment without departing from the scope of the present disclosure to achieve any desired result and will appreciate further features and advantages of the presently disclosed subject matter based on the description provided. Variations, combinations, and/or modifications to any of the embodiments and/or features of the embodiments described herein that are within the abilities of a person having ordinary skill in the art are also within the scope of the present disclosure, as are alternative embodiments that may result from combining, integrating, and/or omitting features from any of the disclosed embodiments.

Use of the term “optionally” with respect to any element of a claim means that the element may be included or omitted, with both alternatives being within the scope of the claim. Additionally, use of broader terms such as “comprises,” “includes,” and “having” should be understood to provide support for narrower terms such as “consisting of,” “consisting essentially of,” and “comprised substantially of.” Accordingly, the scope of protection is not limited by the description set out above, but is defined by the claims that follow, and includes all equivalents of the subject matter of the claims.

In the preceding description, reference may be made to the spatial relationship between the various structures illustrated in the accompanying drawings, and to the spatial orientation of the structures. However, as will be recognized by those skilled in the art after a complete reading of this disclosure, the structures described herein may be positioned and oriented in any manner suitable for their intended purpose. Thus, the use of terms such as “above,” “below,” “upper,” “lower,” “inner,” “outer,” “left,” “right,” “upward,” “downward,” “inward,” “outward,” “horizontal,” “vertical,” etc., should be understood to describe a relative relationship between the structures and/or a spatial orientation of the structures. Those skilled in the art will also recognize that the use of such terms may be provided in the context of the illustrations provided by the corresponding figure(s).

Additionally, terms such as “approximately,” “generally,” “substantially,” and the like should be understood to allow for variations in any numerical range or concept with which they are associated and encompass variations on the order of 25% (e.g., to allow for manufacturing tolerances and/or deviations in design). For example, the term “generally parallel” should be understood as referring to configurations in with the pertinent components are oriented so as to define an angle therebetween that is equal to 180° ± 25% (e.g., an angle that lies within the range of (approximately) 135° to (approximately) 225°). The term “generally parallel” should thus be understood as referring to encompass configurations in which the pertinent components are arranged in parallel relation.

Although terms such as “first,” “second,” “third,” etc., may be used herein to describe various operations, elements, components, regions, and/or sections, these operations, elements, components, regions, and/or sections should not be limited by the use of these terms in that these terms are used to distinguish one operation, element, component, region, or section from another. Thus, unless expressly stated otherwise, a first operation, element, component, region, or section could be termed a second operation, element, component, region, or section without departing from the scope of the present disclosure.

Each and every claim is incorporated as further disclosure into the specification and represents embodiments of the present disclosure. Also, the phrases “at least one of A, B, and C” and “A and/or B and/or C” should each be interpreted to include only A, only B, only C, or any combination of A, B, and C.